Hybrid Flow Shop Scheduling Problems with Multiprocessor Tasks

Abstract

Hybrid flow shop scheduling problems with multiprocessor tasks to minimize the makespan have been addressed and solved efficiently. Several approaches were used, including greedy methods and metaheuristics. In this paper, we proposed a mixed integer programming (MIP) model that can define explicitly and precisely the nature of a given problem. We also addressed a modified lower bound to obtain tighter bounds. Additionally, we propose different decoding methods and emphasize their importance in hybrid flow shop scheduling problems with multiprocessor tasks. By using existing test problems with n=5 in examining the proposed methods, many optimal solutions can be obtained as benchmarks for reference by the MIP model. Accordingly, the results are indicative of the influence of the decoding methods on the solutions to the hybrid flow shop problems with multiprocessor tasks.

Multi-stage appointment scheduling for outpatient chemotherapy unit: a case study

“…Oǧuz et al [27] proposed several lower bounds for a two-stage Hybrid flow shop scheduling with multiprocessor task with arbitrary processing time. Wang et al [40] proposed a mixed integer programming model and derive a tighter lower bound for the same case. Li et al [21] utilized a lower bound based on construction algorithm, they used the proposed lower bound in a branch-and bound algorithm to solve HFSP and study how rescheduling affects surgeons' delays and overtime.…”